评估自动驾驶车辆-行人交互的安全性:一种极值理论方法

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Analytic Methods in Accident Research Pub Date : 2022-09-01 DOI:10.1016/j.amar.2022.100230
Abdul Razak Alozi, Mohamed Hussein
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引用次数: 19

摘要

随着自动驾驶汽车(AV)技术的不断进步,自动驾驶汽车市场份额的预测似乎也在不断增长。这导致了对自动驾驶汽车对其他道路使用者的影响进行主动安全评估的内在需求。为此,本研究提出了一个自动驾驶环境下行人安全主动评估的建模框架。提出的框架依赖于极值理论(EVT)和峰值超过阈值建模技术,利用自动驾驶汽车与行人的冲突来估计自动驾驶汽车与行人的碰撞。拟议的框架应用于从美国和新加坡三个地点收集的两个自动驾驶数据集,使用的是两家开发商(motion和Lyft)的运营自动驾驶车队。这两个数据集都包括受试者自动驾驶汽车的轨迹数据,以及激光雷达点云和自动驾驶汽车摄像头的注释视频数据,以捕捉周围道路使用者的轨迹。对数据集进行处理,提取自动驾驶汽车与行人的冲突以及相应的冲突指标,主要是侵犯后时间(PET)和碰撞时间(TTC)。为了提高模型的性能和预测精度,在模型中引入了相关协变量,包括转弯运动和冲突速度。研究结果表明,行人在与自动驾驶汽车互动时存在令人担忧的风险,尤其是在自动驾驶汽车采用的早期阶段。预计自动驾驶汽车的碰撞次数为每百万车辆公里行驶(VKT) 4至5.5次。随着协变量的增加,预期的碰撞次数下降到每百万VKT 2.3-3.7次,但结果估计的置信区间更窄,拟合更好。所介绍的方法显示了EVT方法在解决自动驾驶汽车安全影响方面的应用前景。它还邀请未来的应用程序来解决不同城市交通条件下的行人安全问题。
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Evaluating the safety of autonomous vehicle–pedestrian interactions: An extreme value theory approach

With the increasing advancements in autonomous vehicle (AV) technologies, the forecasts of AV market shares seem to follow an ever-growing trend. This leads to the inherent need for proactive safety evaluations of AV impacts on other road users. To that end, this study proposes a modeling framework for the proactive assessment of pedestrian safety in AV environments. The proposed framework relies on the Extreme Value Theory (EVT), with the peak over threshold modeling technique, to develop an estimate of AV-pedestrian collisions using AV-pedestrian conflicts. The proposed framework was applied to two AV datasets, collected from three locations in the US and Singapore, using the operating AV fleets of two developers, Motional and Lyft. Both datasets included trajectory data for the subject AV, as well as LiDAR point clouds and annotated video data from AV cameras to capture the trajectories of surrounding road users. The datasets were processed to extract the AV-pedestrian conflicts along with the corresponding conflict indicators, mainly the post-encroachment time (PET) and time-to-collision (TTC). Relevant covariates were introduced to the proposed models to enhance their performance and prediction accuracy, including turning movements and conflict speeds. The results indicate an alarming risk to pedestrians when interacting with AVs, especially at the early stages of AV adoption. The expected number of collisions ranged from 4 to 5.5 per million vehicle kilometers travelled (VKT) of the AVs. With the addition of the covariates, the expected number of collisions went down to a range of 2.3–3.7 per million VKT, but with a narrower confidence interval of the resulting estimate and a better fit. The introduced approach shows promising prospects for the application of EVT methods to address AV safety impacts. It also invites future applications to address issues of concern for pedestrian safety in different conditions of urban traffic.

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来源期刊
CiteScore
22.10
自引率
34.10%
发文量
35
审稿时长
24 days
期刊介绍: Analytic Methods in Accident Research is a journal that publishes articles related to the development and application of advanced statistical and econometric methods in studying vehicle crashes and other accidents. The journal aims to demonstrate how these innovative approaches can provide new insights into the factors influencing the occurrence and severity of accidents, thereby offering guidance for implementing appropriate preventive measures. While the journal primarily focuses on the analytic approach, it also accepts articles covering various aspects of transportation safety (such as road, pedestrian, air, rail, and water safety), construction safety, and other areas where human behavior, machine failures, or system failures lead to property damage or bodily harm.
期刊最新文献
Econometric approaches to examine the onset and duration of temporal variations in pedestrian and bicyclist injury severity analysis Determinants influencing alcohol-related two-vehicle crash severity: A multivariate Bayesian hierarchical random parameters correlated outcomes logit model Effects of sample size on pedestrian crash risk estimation from traffic conflicts using extreme value models Editorial Board A cross-comparison of different extreme value modeling techniques for traffic conflict-based crash risk estimation
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